Rendering algorithms
- Rendering algorithms: Linearization: Gamma, backlight correction, scanner exposure and dark point compensation
- Rendering algorithms: Determining luminosity of each color patch
- Rendering algorithms: Viewing screen alignment
- Rendering algorithms: Viewing screen superposition
- Rendering Modes: Different algorithms used to render the image
- Color models: Different models of colors of dyes of the original process
Scan of original negative 
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Infrared scan of original transparency
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RGB scan of original transparency
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Linearization and inverting negative to positive
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Linearization
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Linearization and channel mixing
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| Linear grayscale transparency
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Viewing screen alignment
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| linear RGB image with viewing screen (see viewing screen superposition) 
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| Determining luminosity of each color patch (optional)
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Blocky linear RGB image (similar to RAW from digital camera)
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| Demosaicing using bicubic interpolation (optional)
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Smooth but unsharp linear RGB image
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| Combining predicted and original data (optional)
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linear RGB image
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| Simulation dyes of viewing screen and conversion to output color profile
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| Digital color rendering
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Realistic simulation of what happens when negative is copied to a transparency in laboratory involves simulating sensitivity curve of the black and white emulsion used. At the moment this step is not implemented in a satisfactory way and we rely on other tools (such as vuescan) to do this job for us. We yet need to understand how typical sensitivity curves were and what kind of user-interface we want to implement here. Ideally we should do this based on scans of existing negative-transparency pairs.
When only RGB scan of a color transparency is available, it is possible to estimate the original black and white transparency by mixing RGB channels to grayscale with a certain weights.
In theory it is possible to recover the infrared channel of the scan using the RGB data.
During digitization light passes from the light source through the filters and the emulsion (which is assumed to be close to neutral density filter) and color filters used on the top of the scanner CCD. Knowing RGB values of the scanner's response to the red, green and blue filters of the color screen it is possible possible to produce 3 equations which makes it possible to compute from scanned RGB value the density of the emulsion. mix_weights.red, mix_weights.green and mix_weights.blue are solution to the equations. Value is further compensated by mix_dark, which should ideally be (0,0,0) but it is practical to offset it in some situation (such as when the value is computed using the actual infrared channel).
The simulated infrared channel is computed as:
ir=(r-mix_dark.red)mix_weights.red+(g-mix_dark.green)mix_weights.green+(b-mix_dark.blue)mix_weights.blue.
Here r, g and b are linearized RGB values of the pixel inspected.
Meaningful of mix_dark are values are in range (-1,1). mix_red, mix_green and mix_blue can be both positive and negative.